Legal claims defining the scope of protection. Each claim is shown in both the original legal language and a plain English translation.
1. A computer-implemented method comprising: receiving, at a vehicle computing system including one or more processors, information indicative of one or more changes in acceleration associated with a plurality of vehicles; receiving, at the vehicle computing system, one or more captured images of a vehicle occupant associated with a given vehicle of the plurality of vehicles; determining, by the one or more processors, that the one or more changes in acceleration exceed an acceleration threshold; accessing, by the vehicle computing system, one or more stored images associated with a seismic event; comparing, by the one or more processors, the one or more captured images to the one or more stored images; based on the comparison, determining, by the one or more processors, a likelihood that the one or more captured images are associated with an occurrence of a seismic event; determining, by the one or more processors, a probability of an occurrence of a seismic event according to (i) the one or more changes in acceleration exceeding the acceleration threshold and (ii) the determined likelihood of the one or more captured images; and based on the probability exceeding a threshold, providing, by the vehicle computing system, an output signal that includes at least the determined probability and location information associated with the plurality of vehicles.
This invention relates to a vehicle-based system for detecting and reporting seismic events by analyzing vehicle acceleration data and occupant imagery. The system monitors acceleration changes across multiple vehicles to identify potential seismic activity. When acceleration exceeds a predefined threshold, the system captures images of vehicle occupants and compares them to stored images associated with known seismic events. By analyzing these comparisons, the system determines the likelihood that the observed acceleration changes and occupant reactions are indicative of a seismic event. The system then calculates a probability of seismic activity based on both the acceleration data and the image analysis. If this probability exceeds a predefined threshold, the system generates an output signal containing the probability and location data from the vehicles, enabling rapid detection and reporting of seismic events. The approach leverages vehicle sensor networks and occupant monitoring to enhance early warning capabilities for earthquakes or other seismic disturbances.
2. The computer-implemented method of claim 1 , wherein the information indicative of one or more changes in acceleration includes one or more changes in a lateral acceleration relative to one or more directions of travel corresponding to the plurality of vehicles.
This invention relates to a computer-implemented method for analyzing vehicle dynamics, specifically focusing on detecting and processing changes in acceleration to improve vehicle control, safety, or navigation systems. The method involves monitoring acceleration data from multiple vehicles to identify lateral acceleration changes relative to their respective directions of travel. Lateral acceleration refers to side-to-side movement, which is critical for understanding vehicle stability, cornering performance, and collision avoidance. By tracking these changes, the system can enhance real-time decision-making, such as adjusting steering, braking, or trajectory planning to prevent accidents or optimize fuel efficiency. The method may also integrate with advanced driver-assistance systems (ADAS) or autonomous driving technologies to provide more responsive and adaptive vehicle behavior. The invention addresses challenges in accurately detecting lateral acceleration variations, which are influenced by factors like road conditions, driver inputs, and external forces. By leveraging data from multiple vehicles, the system improves reliability and accuracy in dynamic environments. The solution is particularly useful for enhancing vehicle safety, performance, and automation in both consumer and commercial applications.
3. The computer-implemented method of claim 1 , wherein determining the likelihood of the one or more captured images further includes: based on the comparison, determining, by the one or more processors, a gesture of the vehicle occupant; and based on the determined gesture, determining, by the one or more processors, the likelihood that the one or more captured images are associated with an occurrence of a seismic event.
This invention relates to a computer-implemented method for analyzing vehicle occupant behavior to detect seismic events. The method addresses the challenge of accurately identifying seismic events by leveraging visual data captured within a vehicle. Traditional seismic detection systems often rely on physical sensors, which may be limited in their ability to distinguish between actual seismic activity and other vibrations. This invention improves upon prior approaches by using image analysis to assess occupant reactions, which can provide more reliable indicators of seismic events. The method involves capturing one or more images of a vehicle occupant using an imaging device, such as a camera. The system then compares the captured images to reference data, which may include predefined gestures or behavioral patterns associated with seismic events. By analyzing these comparisons, the system determines whether the occupant's gestures—such as sudden movements or startled reactions—align with known responses to seismic activity. The likelihood of a seismic event is then calculated based on the presence and nature of these gestures. This approach enhances detection accuracy by incorporating human behavioral cues, which are often more indicative of real seismic events than raw sensor data alone. The method may be integrated into vehicle safety systems to provide early warnings or trigger automated responses.
4. The computer-implemented method of claim 1 , wherein determining the likelihood of the one or more captured images further includes: comparing, by the one or more processors, one or more features of the one or more captured images to one or more features of at least one of the plurality of stored images, wherein the one or more features are associated with one or more facial expressions that correspond to an occurrence of a seismic event; and based on the comparison, determining, by the one or more processors, the likelihood that the one or more captured images are associated with an occurrence of a seismic event.
This invention relates to a computer-implemented method for detecting seismic events by analyzing facial expressions in captured images. The method addresses the challenge of identifying seismic events in real-time or near-real-time by leveraging visual cues from human reactions, which can be more immediate than traditional seismic sensors. The system captures images of individuals and compares their facial expressions to stored reference images associated with known seismic events. The comparison involves analyzing specific facial features, such as eye widening, mouth movements, or other expressions indicative of fear or surprise, which are commonly observed during seismic events. By matching these features to pre-recorded expressions linked to seismic occurrences, the system determines the likelihood that the captured images correspond to an actual seismic event. This approach enhances early detection and response by using human reactions as supplementary data, complementing traditional seismic monitoring systems. The method is particularly useful in areas where traditional sensors are limited or where rapid, localized detection is critical. The system processes the captured images using one or more processors to perform the feature comparison and likelihood determination, ensuring accurate and timely analysis.
5. The computer-implemented method of claim 1 , wherein the information indicative of one or more changes in acceleration includes captured data along one or more axes relative to a direction of travel associated with a vehicle, wherein determining the probability of an occurrence of a seismic event further comprises: determining, by the one or more processors, one or more forces along the one or more axes based on the captured data; determining, by the one or more processors, that one or more characteristics of the one or more forces exceeds a force threshold associated with an occurrence of a seismic event; and based on the determined one or more characteristics exceeding the force threshold, adjusting, by the one or more processors, the determined probability of an occurrence of a seismic event.
This invention relates to a computer-implemented method for detecting and assessing seismic events, such as earthquakes, using vehicle-based sensors. The method addresses the challenge of accurately predicting seismic events by leveraging real-time data from vehicles equipped with motion sensors. The system captures acceleration data along multiple axes relative to the vehicle's direction of travel. This data is processed to determine forces acting on the vehicle, which are then analyzed to detect anomalies indicative of seismic activity. If the measured forces exceed predefined thresholds, the system adjusts the probability of a seismic event occurring. The method improves early warning systems by providing localized, vehicle-derived data that complements traditional seismic monitoring networks. By integrating vehicle sensor data, the system enhances detection accuracy and response times, particularly in areas with sparse seismic instrumentation. The approach is scalable and adaptable to various vehicle types, making it a cost-effective solution for seismic event monitoring.
6. The computer-implemented method of claim 5 , wherein the one or more characteristics include at least one of a frequency, a duration, and an amplitude associated with a given force of the one or more forces.
This invention relates to a computer-implemented method for analyzing forces applied to a system, such as in industrial or robotic applications. The method addresses the challenge of accurately characterizing forces to improve control, safety, or performance in dynamic environments. The invention focuses on extracting specific characteristics of applied forces, including frequency, duration, and amplitude, to enable precise monitoring or response. The method involves detecting one or more forces exerted on a system and measuring their characteristics. Frequency refers to how often the force occurs over time, duration indicates how long the force is applied, and amplitude represents the force's magnitude. By analyzing these parameters, the system can distinguish between different types of forces, such as impacts, vibrations, or sustained pressures. This data can then be used to trigger actions like adjusting robotic movements, activating safety protocols, or optimizing machine operations. The method may also involve comparing the measured force characteristics against predefined thresholds or patterns to identify anomalies or expected behaviors. For example, in a robotic arm, detecting an abnormal amplitude could indicate a collision, prompting an immediate stop. Similarly, monitoring the frequency of vibrations in machinery could help predict maintenance needs. The invention enhances situational awareness and responsiveness in automated systems by providing detailed force analysis.
7. The computer-implemented method of claim 1 , wherein determining the probability of an occurrence of a seismic event further comprises: receiving, at the vehicle computing system, information indicative of vehicle operation of the given vehicle subsequent to the one or more changes in acceleration; and determining, by the one or more processors, the probability of an occurrence of a seismic event according to (i) the one or more changes in acceleration exceeding the acceleration threshold and (ii) the determined likelihood of the one or more captured images, and (iii) the information indicative of vehicle operation.
This invention relates to a computer-implemented method for detecting and assessing the likelihood of seismic events, such as earthquakes, using vehicle-based sensors and data. The method addresses the challenge of early seismic event detection by leveraging vehicle motion and environmental data to improve prediction accuracy. The method involves monitoring a vehicle's acceleration patterns to detect anomalies that may indicate seismic activity. If the vehicle's acceleration exceeds a predefined threshold, the system captures images of the surrounding environment using onboard cameras. These images are analyzed to assess their relevance to seismic event detection, assigning a likelihood score based on factors like ground deformation, structural damage, or other seismic indicators. The system further refines its assessment by analyzing subsequent vehicle operation data, such as braking patterns, steering adjustments, or speed changes, which may correlate with seismic disturbances. The final probability of a seismic event is determined by combining the acceleration data, image analysis results, and vehicle operation metrics. This multi-faceted approach enhances detection reliability by cross-referencing multiple data sources, reducing false positives, and improving early warning capabilities. The method is particularly useful for real-time monitoring in regions prone to seismic activity, enabling timely alerts and safety measures.
8. The computer-implemented method of claim 7 , wherein the information indicative of the vehicle operation includes a braking event subsequent to the one or more changes in acceleration.
A computer-implemented method monitors vehicle operation to detect and analyze braking events following changes in acceleration. The method involves collecting sensor data from a vehicle, such as acceleration, speed, and braking inputs, to identify patterns in vehicle dynamics. Specifically, it tracks one or more changes in acceleration and subsequently detects a braking event, which may indicate a potential safety concern or driver behavior. The system processes this data to determine the relationship between acceleration changes and braking, potentially identifying aggressive driving, sudden stops, or other operational anomalies. The method may integrate with vehicle control systems to adjust responses, such as activating safety features or logging incidents for analysis. By correlating acceleration changes with braking events, the system enhances vehicle safety and performance monitoring, providing insights for predictive maintenance or driver training. The approach leverages real-time data processing to improve situational awareness and response times in automotive applications.
9. The computer-implemented method of claim 1 , wherein determining the probability of an occurrence of a seismic event further comprises: receiving, at the vehicle computing system, information indicative of historical vehicle movement of the given vehicle; determining, by the one or more processors, one or more historical changes in acceleration according to the historical vehicle movement; comparing, by the one or more processors, the one or more historical changes in acceleration to the one or more changes in acceleration; and based on the comparison, adjusting, by the one or more processors, the determined probability of an occurrence of a seismic event.
This invention relates to a computer-implemented method for predicting seismic events, such as earthquakes, using vehicle movement data. The method addresses the challenge of improving the accuracy of seismic event predictions by leveraging real-time and historical vehicle movement data to detect subtle ground vibrations that may precede seismic activity. The method involves a vehicle computing system that receives real-time vehicle movement data, including changes in acceleration, from one or more vehicles. The system analyzes these changes to detect patterns that may indicate seismic activity. To enhance prediction accuracy, the system also receives historical vehicle movement data for the same vehicle and identifies historical changes in acceleration. By comparing the historical and real-time acceleration changes, the system adjusts the probability of a seismic event occurring. This comparison helps distinguish between normal vehicle movements and potential seismic signals, reducing false positives and improving reliability. The method integrates vehicle sensor data with seismic prediction algorithms, providing a novel approach to early detection of seismic events.
10. The computer-implemented method of claim 1 , wherein determining the probability of an occurrence of a seismic event further comprises: determining, by the one or more processors, whether the one or more changes in acceleration exceed a first threshold associated with a lateral acceleration relative to a direction of travel; receiving, at the vehicle computing system, information indicative of vehicle operation of the given vehicle subsequent to the one or more changes in acceleration; based on the information indicative of vehicle operation of the given vehicle, determining, by the one or more processors, whether one or more subsequent changes in acceleration exceed a second threshold associated with a deceleration of the given vehicle; and based on exceeding (i) the first threshold and (ii) the second threshold, adjusting, by the one or more processors, the determined probability of an occurrence of a seismic event.
This invention relates to a computer-implemented method for detecting and assessing seismic events, particularly in the context of vehicle operation. The method addresses the challenge of accurately predicting seismic events by analyzing vehicle motion data to determine the likelihood of such occurrences. The system monitors changes in a vehicle's acceleration, specifically evaluating whether these changes exceed predefined thresholds. The first threshold pertains to lateral acceleration relative to the vehicle's direction of travel, while the second threshold assesses deceleration. If both thresholds are exceeded, the system adjusts the probability of a seismic event occurring. Additionally, the method evaluates subsequent vehicle operation data to refine this probability assessment. The invention enhances seismic event detection by leveraging real-time vehicle dynamics, improving accuracy in identifying potential seismic activity. This approach integrates vehicle motion analysis with probabilistic modeling to provide a more reliable assessment of seismic risks. The system processes acceleration data, compares it against thresholds, and adjusts event probabilities based on the results, offering a dynamic and responsive method for seismic event prediction.
11. A system comprising: one or more computing devices; and a non-transitory computer-readable memory coupled to the one or more computing devices and storing thereon instructions, that when executed by the one or more computing devices, cause the one or more computing devices to: receive information indicative of one or more changes in acceleration associated with a plurality of vehicles; receive one or more captured images of a vehicle occupant associated with a given vehicle of the plurality of vehicles; determine that the one or more changes in acceleration exceed an acceleration threshold; access one or more stored images associated with a seismic event; compare the one or more captured images to the one or more stored images; based on the comparison, determine a likelihood that the one or more captured images are associated with an occurrence of a seismic event; determine a probability of an occurrence of a seismic event according to (i) the one or more changes in acceleration exceeding the acceleration threshold and (ii) the determined likelihood of the one or more captured images; and based on the probability exceeding a threshold, provide an output signal that includes at least the determined probability and location information associated with the plurality of vehicles.
This system detects and confirms seismic events using vehicle data. The technology addresses the challenge of accurately identifying seismic events in real-time by leveraging vehicle sensors and occupant imaging. The system receives acceleration data from multiple vehicles, analyzing changes to detect potential seismic activity. Simultaneously, it captures images of vehicle occupants to assess their reactions, which may indicate a seismic event. If acceleration changes exceed a predefined threshold, the system compares occupant images to stored images associated with known seismic events. By analyzing both acceleration data and image comparisons, the system calculates a probability of a seismic event occurring. If this probability surpasses a set threshold, the system generates an output signal containing the probability and vehicle location data, enabling rapid detection and response. The integration of sensor data and visual analysis improves accuracy over traditional seismic detection methods, particularly in urban areas where vehicle networks are dense. This approach enhances early warning systems by providing real-time, location-specific seismic event confirmation.
12. The system of claim 11 , wherein the information indicative of one or more changes in acceleration includes one or more changes in a lateral acceleration relative to one or more directions of travel corresponding to the plurality of vehicles.
This invention relates to a vehicle monitoring system that detects and analyzes changes in acceleration, particularly lateral acceleration, to improve safety and performance. The system tracks multiple vehicles and measures their acceleration patterns, focusing on lateral acceleration relative to their travel directions. By monitoring these changes, the system can identify potential hazards, optimize vehicle dynamics, or enhance navigation algorithms. The lateral acceleration data helps distinguish between normal driving conditions and abnormal events, such as sudden swerves or collisions. The system may use sensors or external data sources to gather acceleration information and process it in real-time or offline. This approach enables applications in autonomous driving, fleet management, or traffic safety by providing insights into vehicle behavior and environmental interactions. The invention addresses the need for more precise and context-aware acceleration monitoring to reduce accidents and improve vehicle control.
13. The system of claim 11 , wherein the instructions that cause the one or more computing devices to determine determining the likelihood of the one or more captured images further include instructions to: based on the comparison, determine a gesture of the vehicle occupant; and based on the determined gesture, determine the likelihood that the one or more captured images are associated with an occurrence of a seismic event.
A system for analyzing vehicle occupant behavior to detect seismic events involves capturing images of a vehicle occupant using one or more cameras. The system processes these images to compare the occupant's gestures against predefined gesture patterns associated with seismic events, such as earthquakes. By analyzing the occupant's movements, the system determines whether the gestures match those typically observed during seismic activity. The likelihood of a seismic event is then calculated based on this comparison. The system may also incorporate additional data, such as sensor inputs or environmental conditions, to refine the assessment. This approach enables early detection of seismic events by leveraging occupant behavior as an indirect indicator, providing a supplementary method for seismic monitoring in vehicles. The system is designed to enhance safety by alerting occupants or triggering automated responses if a seismic event is detected.
14. The system of claim 11 , wherein the instructions that cause the one or more computing devices to determine determining the likelihood of the one or more captured images further include instructions to: compare one or more features of the one or more captured images to one or more features of at least one of the plurality of stored images, wherein the one or more features are associated with one or more facial expressions that correspond to an occurrence of a seismic event; and based on the comparison, determine the likelihood that the one or more captured images are associated with an occurrence of a seismic event.
This invention relates to a system for detecting seismic events by analyzing facial expressions in captured images. The system addresses the challenge of accurately identifying seismic events by leveraging human reactions, which can provide early or supplementary indicators of such events. The system includes one or more computing devices configured to process images captured by cameras, comparing features of these images to stored reference images. The stored images contain facial expressions associated with seismic events, such as fear, surprise, or distress, which are indicative of an individual's reaction to seismic activity. The system analyzes the captured images to extract features like facial landmarks, expressions, or other visual cues and compares them to the stored reference images. By matching these features, the system determines the likelihood that the captured images correspond to a seismic event. The comparison process may involve machine learning algorithms, pattern recognition, or other analytical techniques to assess similarity. The system's ability to detect seismic events through human reactions offers a complementary approach to traditional seismic monitoring methods, potentially improving early warning systems.
15. The system of claim 11 , wherein the information indicative of one or more changes in acceleration includes captured data along one or more axes relative to a direction of travel associated with a vehicle, wherein the instructions that cause the one or more computing devices to determine the probability of an occurrence of a seismic event further include instructions to: determine one or more forces along the one or more axes based on the captured data; and determine that one or more characteristics of the one or more forces exceeds a force threshold associated with an occurrence of a seismic event; and based on the determined one or more characteristics exceeding the force threshold, adjust the determined probability of an occurrence of a seismic event.
This invention relates to a system for detecting and predicting seismic events, such as earthquakes, by analyzing vehicle motion data. The system addresses the challenge of early seismic event detection by leveraging existing vehicle sensors to capture acceleration data along multiple axes relative to the vehicle's direction of travel. The captured data is processed to determine forces acting on the vehicle along these axes. The system then evaluates whether these forces exceed predefined thresholds associated with seismic activity. If the forces surpass the threshold, the system adjusts the probability of a seismic event occurring, providing an early warning. This approach enhances seismic monitoring by utilizing vehicle-based sensors, which are widely available and can provide real-time data across large geographic areas. The system improves upon traditional seismic detection methods by offering a distributed, vehicle-based network that can detect subtle ground movements indicative of impending seismic events. The invention also includes mechanisms to filter out non-seismic forces, ensuring accurate event prediction.
16. The system of claim 15 , wherein the one or more characteristics include at least one of a frequency, a duration, and an amplitude associated with a given force of the one or more forces.
This invention relates to a system for analyzing forces applied to a surface, such as a touch-sensitive interface or a structural component, to detect and characterize interactions. The system addresses the challenge of accurately identifying and interpreting dynamic forces, such as those generated by touch, pressure, or impact, to improve responsiveness and functionality in applications like user interfaces, industrial monitoring, or safety systems. The system includes sensors configured to detect forces applied to a surface and generate corresponding signals. These signals are processed to extract one or more characteristics of the forces, including frequency, duration, and amplitude. By analyzing these characteristics, the system can distinguish between different types of interactions, such as taps, swipes, or sustained pressure, and trigger appropriate responses. For example, in a touch-sensitive device, the system may differentiate between a light tap and a firm press to enable multi-modal input. In industrial applications, it may monitor structural integrity by detecting abnormal force patterns. The system may also include a controller that processes the sensor signals to filter noise, normalize data, or apply machine learning models to classify force patterns. The extracted characteristics can be used to adjust system behavior, such as modifying sensitivity thresholds or activating safety protocols. The invention enhances precision in force-based interactions, improving user experience and system reliability in various domains.
17. The system of claim 11 , wherein the instructions that cause the one or more computing devices to determine the probability of an occurrence of a seismic event further include instructions to: receive information indicative of vehicle operation of the given vehicle subsequent to the one or more changes in acceleration; and determine the probability of an occurrence of a seismic event according to (i) the one or more changes in acceleration exceeding the acceleration threshold and (ii) the determined likelihood of the one or more captured images, and (iii) the information indicative of vehicle operation.
This invention relates to a system for detecting and predicting seismic events, such as earthquakes, by analyzing vehicle motion and sensor data. The system addresses the challenge of early seismic event detection by leveraging data from vehicles equipped with sensors, such as accelerometers and cameras, to identify patterns that may indicate an impending seismic event. The system monitors changes in vehicle acceleration and compares them to predefined thresholds. If the acceleration exceeds these thresholds, the system further evaluates the likelihood of the seismic event based on captured images and subsequent vehicle operation data. The system integrates these factors—acceleration changes, image analysis, and vehicle operation—to compute a probability of a seismic event occurring. This approach enhances early warning capabilities by using real-time vehicle data to improve detection accuracy and reliability. The system is designed to process and analyze this data efficiently, providing timely alerts to mitigate potential risks associated with seismic events.
18. The system of claim 17 , wherein the information indicative of the vehicle operation includes a braking event subsequent to the one or more changes in acceleration.
A system monitors vehicle operation to detect and analyze braking events following changes in acceleration. The system collects data from vehicle sensors, including acceleration and braking patterns, to identify correlations between acceleration changes and subsequent braking actions. This helps assess driver behavior, vehicle performance, and potential safety risks. The system processes the data to determine whether braking events are related to prior acceleration changes, such as sudden acceleration followed by hard braking. By analyzing these patterns, the system can detect aggressive driving, mechanical issues, or other anomalies. The system may also compare the data against predefined thresholds or historical trends to identify deviations. The analysis can be used for fleet management, driver training, or predictive maintenance. The system may include a data processing unit, sensors, and a storage module to record and analyze the vehicle operation data. The braking event data is used to refine safety protocols or adjust vehicle settings to improve performance and reduce risks.
19. The system of claim 11 , wherein the instructions that cause the one or more computing devices to determine the probability of an occurrence of a seismic event further include instructions to: receive information indicative of historical vehicle movement of the given vehicle; determine one or more historical changes in acceleration according to the historical vehicle movement; compare the one or more historical changes in acceleration to the one or more changes in acceleration; and based on the comparison, adjust, the determined probability of an occurrence of a seismic event.
This invention relates to a system for predicting seismic events, such as earthquakes, by analyzing vehicle movement data. The system addresses the challenge of detecting early signs of seismic activity by leveraging real-time and historical vehicle motion patterns, which may indicate ground disturbances. The system includes one or more computing devices configured to receive sensor data from vehicles, such as accelerometers, to detect changes in acceleration. These changes are analyzed to determine the likelihood of a seismic event occurring. The system further refines this probability by comparing current acceleration changes to historical vehicle movement data, adjusting the prediction based on past patterns. This approach enhances the accuracy of seismic event forecasting by incorporating both real-time and historical vehicle dynamics, providing an early warning system for potential seismic activity. The system may also include additional components, such as data processing modules and communication interfaces, to collect, analyze, and transmit the relevant information. The use of vehicle sensor data offers a novel method for seismic monitoring, particularly in areas where traditional seismic sensors are sparse.
20. The system of claim 11 , wherein the instructions that cause the one or more computing devices to determine the probability of an occurrence of a seismic event further include instructions to: determine whether the one or more changes in acceleration exceed a first threshold associated with a lateral acceleration relative to a direction of travel; receive information indicative of vehicle operation of the given vehicle subsequent to the one or more changes in acceleration; based on the information indicative of vehicle operation of the given vehicle, determine whether one or more subsequent changes in acceleration exceed a second threshold associated with a deceleration of the given vehicle; and based on exceeding (i) the first threshold and (ii) the second threshold, adjust the determined probability of an occurrence of a seismic event.
This invention relates to a system for detecting and assessing the likelihood of seismic events, such as earthquakes, by analyzing vehicle acceleration data. The system monitors changes in a vehicle's acceleration to identify patterns that may indicate seismic activity. Specifically, the system determines whether lateral acceleration changes exceed a predefined threshold relative to the vehicle's direction of travel. If this threshold is exceeded, the system then evaluates subsequent deceleration changes based on vehicle operation data. If these deceleration changes also exceed a second threshold, the system adjusts the probability of a seismic event occurring. The system uses this multi-stage analysis to improve the accuracy of seismic event detection by correlating vehicle motion data with potential seismic disturbances. The invention is particularly useful for early warning systems that rely on real-time data from vehicles to detect and assess seismic risks.
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July 7, 2020
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